Is it possible to retrieve only sub document from an object array in MongoDB collection which matches specified query Using REST HTTP interface.
There are many already answer for similar questions, but those are for using MongoDB driver, not REST/HTTP
Any possibility ?
Sample data
[
{
"name":"Paul",
"addresses":[
{
"addressline1":"Street no1",
"city":"Delhi"
},
{
"addressline1":"Street no4",
"city":"Chennai"
}
]
},
{
"name":"Rose",
"addresses":[
{
"addressline1":"Street no5",
"city":"Delhi"
},
{
"addressline1":"Street no7",
"city":"Chennai"
}
]
}
]
From above data I only need to get single address, which 'name' matching 'Paul' and 'city' matching 'Delhi' as below
{
"addressline1":"Street no1",
"city":"Delhi"
}
I have below query to search within sub document. But it returns all elements in sub document array which contains this sub document query.
https://api.mongolab.com/api/1/databases/[mydb]/collections/[mycollection?
apiKey=[myAPIKey]
&q={"name":"Paul","addresses.city":{"$regex":"^Delhi$","$options":"i"}}
&f={"addresses":1}
But above query returns
{
"addresses":[
{
"addressline1":"Street no1",
"city":"Delhi"
},
{
"addressline1":"Street no4",
"city":"Chennai"
}
]
}
Try this:
https://...&f={"addresses.$":1}
Note that I used the $ projection operator in the query above.
Related
Currently, that's my current document:
{
_id: 'd283015f-91e9-4404-9202-093c28d6a931',
referencedGeneralPractitioner: [
{
resourceType: 'practitioner',
cachedIdentifier: [
{
system: { value: 'urn:oid:1.3.6.1.4.1.19126.3' },
value: { value: '14277399B' }
}
]
}
]
}
Here, there's two nested objects arrays: referencedGeneralPractitioner[{cachedIdentifier[{}]}].
Currently, I'm getting results using this query:
{
"referencedGeneralPractitioner":{
"$elemMatch":{
"cachedIdentifier.value.value":"14277399B",
"cachedIdentifier.system.value":"urn:oid:1.3.6.1.4.1.19126.3"
}
}
}
It's getting my desired document, but I don't quite figure out if above query is which I'm really looking for.
I mean, I'm only applying $elemMatch on referencedGeneralPractitioner field array.
Is it really enought?
Should I add a nested $elemMatch on cachedIdentifier?
Any ideas?
It looks like you need to query it like this:
db.collection.find({
"referencedGeneralPractitioner.cachedIdentifier": {
"$elemMatch": {
"value.value": "14277399B",
"system.value": "urn:oid:1.3.6.1.4.1.19126.3"
}
}
})
playground
This is in case you need to find the full document having $and of both values in same element in any of the elements in the nested array , if you need to extract specific element you will need to $filter
if you need to search also based on element in the 1st array level then you need to modify as follow:
{
"referencedGeneralPractitioner": {
"$elemMatch": {
resourceType: 'practitioner',
"cachedIdentifier": {
"$elemMatch": {
"value.value": 1,
"system.value":2
}
}
}
}
}
This will give you all full documents where at same time there is resouceType:"practitioner" and { value.value:3 and system.value: 2 }
Also is important to stress that this will not gona work correctly!:
{
"referencedGeneralPractitioner":{
"$elemMatch":{
"cachedIdentifier.value.value":"14277399B",
"cachedIdentifier.system.value":"urn:oid:1.3.6.1.4.1.19126.3"
}
}
}
Since it will match false positives based on any single value in the nested elements like:
wrong playground
Given collection:
{
"_id" : "1.1000038",
"recomendation" : [
"1.6739718"
]
}
/* 2 */
{
"_id" : "1.1000069",
"recomendation" : [
"1.9185509",
"1.9051998",
"1.9034279",
"1.8288046",
"1.8152670",
"1.858775",
"1.6224229",
"1.4591674",
"1.3862464",
"1.3427739",
"1.3080062",
"1.3003608",
"1.1694619",
"1.1634683",
"1.1590664",
"1.1524146",
"1.754599",
"1.700837",
"1.763617"
]
}
I need to query the MongoDB for a list of values and get the first element of the list of values
here is the query by mongo syntax
db.getCollection('similar_articles').find({"_id":{$in:["1.1000069","1.1000038"]}})
I don't want to filter it on the python side because it's can be too big.
I didn't find any documentation on it
desire output:
Pandas DataFrame
_id recom
1.1000038 1.6739718
1.1000069 1.9185509
I don't know pymongo so well, but you need this query:
First $match by _ids into the arreay (this is like the find you have).
And later use $project to create the field recom (you can use "recomendation" to overwrite the existing field) and set the value as the first into the array.
db.collection.aggregate([
{
"$match": { "_id": { "$in": [ "1.1000069", "1.1000038" ] } }
},
{
"$project": { "recom": { "$arrayElemAt": [ "$recomendation", 0 ] } }
}
])
Example here
Looking the doumentation it seems you only need to copy and paste this query.
My document in MongoDB is like this:
{
"data":{
"groupName":"sample",
"users": [
{
"_id":new ObjectId(),
"mobNum":"29857903289",
"isAdmin":"true"
},
{
"_id":new ObjectId(),
"mobNum":"87532480923",
"isAdmin":"false"
},
]
}
}
users is an array of embedded-ducuments in groupusers collection. When I try to query the embedded sub field like this
db.groupusers.find( { "users.$.mobNum": "29857903289" } ), it returns me no response.
Problem is in querying the embedded sub field. I'm new to use MongoDB. Don't know how to query the embedded array of sub field. Not sure what to do. Any help is appreciated.
Here use this
db.getCollection('YOUR_COLLECTION_HERE').find({
"data.users": {
"$elemMatch": {
"mobNum": "29857903289"
}
}
}})
given a document structure as shown, where the trades array can have thousands of items... how on earth could one do a query that would verify that the sequence always has 'startTradeId' one number higher than the previous items 'endTradeId', all the way through the array? is this even possible?
{
"name": "STOCK",
"trades": [{
"endTradeId": 41306,
"startTradeId": 41302,
...
},
{
"endTradeId": 41301,
"startTradeId": 41297,
...
},
{
"endTradeId": 41296,
"startTradeId": 41240,
...
},
...
]
}
You can use $where operator like below :
db.your_collection.find( { $where : function(){ return "this.trades.startTradeId > this.trades.endTradeId" }});
I have a MongoDB collection with data in the format of:
[
{
"data1":1,
"data2":2,
"data3":3,
"data4":4,
"horses":[
{
"opponent":{
"jockey":"MyFirstName MyLastName",
"name":"MyHorseName",
"age":4,
"sex":"g",
"scratched":"false",
"id":"1"
},
"id":"1"
},
{
"opponent":{
"jockey":"YourFirstName YourLastName",
"name":"YourHorseName",
"age":4,
"sex":"m",
"scratched":"false",
"id":"2"
},
"id":"2"
}
]
},
...
]
Executing the following query returns exactly what I need:
db.race_results.find({ "$and": [ { "horses":
{ "$elemMatch": { "$and": [
{ "opponent.name": "MyFirstName MyLastName" },
{ "opponent.jockey": "MyHorseName"}
] } }
}
]})
However, this query takes 0.5 seconds to execute with my collection (there are a lot of records).
I am trying to find out how to create an index on the horses.opponent.name field of the data. I have read the docs about multikey indexes (here), but I'm not sure if this is exactly what I need or not. What I need (I think) is an index on the array element of horses, but only the name and jockey fields. Is this possible?
Is there a way to create an index to make my specific query (the one above) any faster?
Any pointers would be greatly appreciated. I am fairly new to MongoDB, but learning fast!
The index to create is:
db.race_results.ensureIndex({"horses.opponent.name":1, "horses.opponent.jockey":1})
After creating this index, the query in your case should return number of scanned objects that is equal to the number of matched objects:
db.race_results.find( { horses: { $elemMatch: { "opponent.name": "MyHorseName", "opponent.jockey": "MyFirstName MyLastName" } } }
).explain()